As marketing analysts, we are focused on delivering excellence in all things analytical, whether a basic profiling exercise to provide our clients with more insight into what their customers look like, or a suite of sophisticated predictive models that identify who is most likely to act in a given campaign. An important part of our work is making sure we have strong relationships with and are collaborating with our clients as well as our internal strategy and technology experts to be sure that the analysis fits within the bigger picture. And that’s where good strategy comes into play.

Throughout the book, Rumelt gives many specific examples that highlight the good and the bad. He explores ten ‘sources of power’ used to develop good strategy. In the table below, I have highlighted several sources of power, each with an application to marketing analytics.

Good Strategy: Sources of Power

Application to Marketing Analytics

It’s critical to make sure all the individual parts within a chain link systemwork together as a whole. There is no point in optimizing one link if the subsequent one is broken.An example of this is providing expert-level tools to untrained people.

Most, if not all, analytical projects start with data. It’s important to qualify data sources and fields before integrating them into a solution. A single data field that is erroneuosly populated or incorrectly interpreted can undermine the value of the entire project. A critical objective during the project discovery stage is to collaborate with your internal as well as client teams to share findings and validate assumptions you make. An output of this process is an integrated and useable data set and supporting business rules which have been vetted by the team.

Focusis a term often used when describing strategy. Rumelt explores the concept of hidden focus as a competitive advantage. In this case the true, underlying focus may not be evident to the marketplace and yet it delivers advantage.An example is a manufacturing firm that sells what appears to be a commodity but develops a niche with its faster turnaround and lower order sizes.

For any analyst dealing with vast amounts of data, focus is a core part of our daily work. The process we use to decide what to pay attention to and what to ignore is largly influenced by what we have done before. The benefits of a repeatable process should be complemented with an open mind to new ideas. Pausing, validating that the analysis fits the broader strategy, and applying a fresh perspective in which we challenge some of our underlying assumptions can uncover a hidden focus and new insight in our work.

In situations with a high degree of complexity, develop a proximate objectivewhich takes a complex strategy and simplifies it into a solvable problem, one that is "good enough" and enables positive movement.For example, following Kennedy’s challenge to land on the moon, engineers were given specifications that described the moon’s surface as being very much like the desert. This was a proximate objective that allowed the team to move forward.

A predictive model that identifies likely responders needs to fit into an overall strategy that makes it actionable and measurable. A simpler "good enough" model may be preferable, especially if part of the implementation process is to engage and educate management and users about how the model works. In this scenario a more complex and accurate model might never pass the adoption stage.

Do More With Your Data.

SIGMA Marketing Insights is a boutique marketing services firm obsessed with the customer experience, and driven to turn data into a powerful tool that will deliver more relevant, personalized interaction and engagement across all channels.